Zeng Youjie, Huang Jun, Guo Ren, Cao Si, Yang Heng, Ouyang Wen
Department of Anesthesiology, Third Xiangya Hospital, Central South University, Changsha, China.
Department of Pharmacy, Third Xiangya Hospital, Central South University, Changsha, China.
Front Genet. 2023 Feb 27;14:1058582. doi: 10.3389/fgene.2023.1058582. eCollection 2023.
Idiopathic pulmonary fibrosis (IPF) is a fatal and irreversible interstitial lung disease. The specific mechanisms involved in the pathogenesis of IPF are not fully understood, while metabolic dysregulation has recently been demonstrated to contribute to IPF. This study aims to identify key metabolism-related genes involved in the progression of IPF, providing new insights into the pathogenesis of IPF. We downloaded four datasets (GSE32537, GSE110147, GSE150910, and GSE92592) from the Gene Expression Omnibus (GEO) database and identified differentially expressed metabolism-related genes (DEMRGs) in lung tissues of IPF by comprehensive analysis. Then, we performed GO, KEGG, and Reactome enrichment analyses of the DEMRGs. Subsequently, key DEMRGs were identified by machine-learning algorithms. Next, miRNAs regulating these key DEMRGs were predicted by integrating the GSE32538 (IPF miRNA dataset) and the miRWalk database. The Cytoscape software was used to visualize miRNA-mRNA regulatory networks. In addition, the relative levels of immune cells were assessed by the CIBERSORT algorithm, and the correlation of key DEMRGs with immune cells was calculated. Finally, the mRNA expression of the key DEMRGs was validated in two external independent datasets and an experiment. A total of 101 DEMRGs (51 upregulated and 50 downregulated) were identified. Six key DEMRGs (ENPP3, ENTPD1, GPX3, PDE7B, PNMT, and POLR3H) were further identified using two machine-learning algorithms (LASSO and SVM-RFE). In the lung tissue of IPF patients, the expression levels of ENPP3, ENTPD1, and PDE7B were upregulated, and the expression levels of GPX3, PNMT, and POLR3H were downregulated. In addition, the miRNA-mRNA regulatory network of key DEMRGs was constructed. Then, the expression levels of key DEMRGs were validated in two independent external datasets (GSE53845 and GSE213001). Finally, we verified the key DEMRGs in the lung tissue of bleomycin-induced pulmonary fibrosis mice by qRT-PCR. Our study identified key metabolism-related genes that are differentially expressed in the lung tissue of IPF patients. Our study emphasizes the critical role of metabolic dysregulation in IPF, offers potential therapeutic targets, and provides new insights for future studies.
特发性肺纤维化(IPF)是一种致命且不可逆的间质性肺疾病。IPF发病机制中涉及的具体机制尚未完全明确,而最近已证明代谢失调与IPF有关。本研究旨在确定参与IPF进展的关键代谢相关基因,为IPF的发病机制提供新的见解。我们从基因表达综合数据库(GEO)下载了四个数据集(GSE32537、GSE110147、GSE150910和GSE92592),并通过综合分析确定IPF肺组织中差异表达的代谢相关基因(DEMRGs)。然后,我们对DEMRGs进行了基因本体(GO)、京都基因与基因组百科全书(KEGG)和Reactome富集分析。随后,通过机器学习算法确定关键DEMRGs。接下来,通过整合GSE32538(IPF miRNA数据集)和miRWalk数据库预测调控这些关键DEMRGs的miRNA。使用Cytoscape软件可视化miRNA-mRNA调控网络。此外,通过CIBERSORT算法评估免疫细胞的相对水平,并计算关键DEMRGs与免疫细胞的相关性。最后,在两个外部独立数据集和一项实验中验证关键DEMRGs的mRNA表达。共鉴定出101个DEMRGs(51个上调和50个下调)。使用两种机器学习算法(套索回归和支持向量机递归特征消除法)进一步确定了六个关键DEMRGs(ENPP3、ENTPD1、GPX3、PDE7B、PNMT和POLR3H)。在IPF患者的肺组织中,ENPP3、ENTPD1和PDE7B的表达水平上调,而GPX3、PNMT和POLR3H的表达水平下调。此外,构建了关键DEMRGs的miRNA-mRNA调控网络。然后,在两个独立的外部数据集(GSE53845和GSE213001)中验证关键DEMRGs的表达水平。最后,我们通过定量逆转录聚合酶链反应(qRT-PCR)在博来霉素诱导的肺纤维化小鼠的肺组织中验证了关键DEMRGs。我们的研究确定了在IPF患者肺组织中差异表达的关键代谢相关基因。我们的研究强调了代谢失调在IPF中的关键作用,提供了潜在的治疗靶点,并为未来的研究提供了新的见解。